Cargando…
1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database
BACKGROUND: Pre-exposure prophylaxis (PrEP) in the form of daily tenofovir disoproxil fumarate (TDF/FTC) is a potentially transformative tool to prevent HIV infection. However, PrEP scale-up in the United States has been slow and difficult to evaluate comprehensively. All payer claims databases (APC...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808866/ http://dx.doi.org/10.1093/ofid/ofz360.1141 |
_version_ | 1783461841354096640 |
---|---|
author | Nocka, Kristen Raifman, Julia Crowley, Christina Galárraga, Omar Wilson, Ira Tao, Jun Chan, Philip Chan, Philip |
author_facet | Nocka, Kristen Raifman, Julia Crowley, Christina Galárraga, Omar Wilson, Ira Tao, Jun Chan, Philip Chan, Philip |
author_sort | Nocka, Kristen |
collection | PubMed |
description | BACKGROUND: Pre-exposure prophylaxis (PrEP) in the form of daily tenofovir disoproxil fumarate (TDF/FTC) is a potentially transformative tool to prevent HIV infection. However, PrEP scale-up in the United States has been slow and difficult to evaluate comprehensively. All payer claims databases (APCDs) are large datasets that contain information on medical and pharmaceutical claims from most public and private payers in each state, and provide an unusual opportunity to evaluate statewide PrEP implementation efforts. METHODS: We used 2012–2017 data from Rhode Island’s APCD and developed an algorithm to identify individuals prescribed TDF/FTC for PrEP. We compared APCD PrEP data to electronic medical record (EMR) data at the largest dedicated PrEP program in the state, and to other comprehensive pharmaceutical claims data (AIDSVu.org). We calculated the PrEP-to-Need ratio (PnR) based on annual HIV incidence, and used multivariable logistic regression to predict ZIP code-level PrEP use, and specialty of prescribing provider (primary care vs. infectious disease). RESULTS: The Rhode Island APCD included insurance claims for 917,633 individuals (87% of the Rhode Island population). PrEP use increased substantially in Rhode Island over the 5-year period, from 13 to 331 prescriptions between 2012 and 2017, with 546 total users during this time period. Users were predominantly male (89%) and privately insured (69.1%), and concentrated in Providence County (71.5%). The PnR ratio increased from 0.2 to 4.0 from 2012–2017. Compared with AIDSVu and EMR Data, the APCD underestimated the number of PrEP users in Rhode Island, but improved over time in documenting users. Infectious diseases specialists had 8.4 times the odds (95% CI: 5.4 to 12.9) of being a PrEP prescriber compared with primary care providers. A total of 2.6% of infectious disease specialists were PrEP prescribers compared with 0.33% of PCPs. The proportion of Black or Hispanic individuals in a ZIP-code was not a significant predictor of PrEP use. CONCLUSION: APCDs offer an innovative approach to evaluate statewide PrEP implementation comprehensively. Engaging PCPs in PrEP implementation is critical to improve overall uptake among populations most at-risk. [Image: see text] DISCLOSURES: All authors: No reported disclosures. |
format | Online Article Text |
id | pubmed-6808866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68088662019-10-28 1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database Nocka, Kristen Raifman, Julia Crowley, Christina Galárraga, Omar Wilson, Ira Tao, Jun Chan, Philip Chan, Philip Open Forum Infect Dis Abstracts BACKGROUND: Pre-exposure prophylaxis (PrEP) in the form of daily tenofovir disoproxil fumarate (TDF/FTC) is a potentially transformative tool to prevent HIV infection. However, PrEP scale-up in the United States has been slow and difficult to evaluate comprehensively. All payer claims databases (APCDs) are large datasets that contain information on medical and pharmaceutical claims from most public and private payers in each state, and provide an unusual opportunity to evaluate statewide PrEP implementation efforts. METHODS: We used 2012–2017 data from Rhode Island’s APCD and developed an algorithm to identify individuals prescribed TDF/FTC for PrEP. We compared APCD PrEP data to electronic medical record (EMR) data at the largest dedicated PrEP program in the state, and to other comprehensive pharmaceutical claims data (AIDSVu.org). We calculated the PrEP-to-Need ratio (PnR) based on annual HIV incidence, and used multivariable logistic regression to predict ZIP code-level PrEP use, and specialty of prescribing provider (primary care vs. infectious disease). RESULTS: The Rhode Island APCD included insurance claims for 917,633 individuals (87% of the Rhode Island population). PrEP use increased substantially in Rhode Island over the 5-year period, from 13 to 331 prescriptions between 2012 and 2017, with 546 total users during this time period. Users were predominantly male (89%) and privately insured (69.1%), and concentrated in Providence County (71.5%). The PnR ratio increased from 0.2 to 4.0 from 2012–2017. Compared with AIDSVu and EMR Data, the APCD underestimated the number of PrEP users in Rhode Island, but improved over time in documenting users. Infectious diseases specialists had 8.4 times the odds (95% CI: 5.4 to 12.9) of being a PrEP prescriber compared with primary care providers. A total of 2.6% of infectious disease specialists were PrEP prescribers compared with 0.33% of PCPs. The proportion of Black or Hispanic individuals in a ZIP-code was not a significant predictor of PrEP use. CONCLUSION: APCDs offer an innovative approach to evaluate statewide PrEP implementation comprehensively. Engaging PCPs in PrEP implementation is critical to improve overall uptake among populations most at-risk. [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6808866/ http://dx.doi.org/10.1093/ofid/ofz360.1141 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Abstracts Nocka, Kristen Raifman, Julia Crowley, Christina Galárraga, Omar Wilson, Ira Tao, Jun Chan, Philip Chan, Philip 1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database |
title | 1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database |
title_full | 1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database |
title_fullStr | 1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database |
title_full_unstemmed | 1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database |
title_short | 1278. Assessing Statewide HIV Pre-exposure Prophylaxis Implementation Using an All Payer Claims Database |
title_sort | 1278. assessing statewide hiv pre-exposure prophylaxis implementation using an all payer claims database |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808866/ http://dx.doi.org/10.1093/ofid/ofz360.1141 |
work_keys_str_mv | AT nockakristen 1278assessingstatewidehivpreexposureprophylaxisimplementationusinganallpayerclaimsdatabase AT raifmanjulia 1278assessingstatewidehivpreexposureprophylaxisimplementationusinganallpayerclaimsdatabase AT crowleychristina 1278assessingstatewidehivpreexposureprophylaxisimplementationusinganallpayerclaimsdatabase AT galarragaomar 1278assessingstatewidehivpreexposureprophylaxisimplementationusinganallpayerclaimsdatabase AT wilsonira 1278assessingstatewidehivpreexposureprophylaxisimplementationusinganallpayerclaimsdatabase AT taojun 1278assessingstatewidehivpreexposureprophylaxisimplementationusinganallpayerclaimsdatabase AT chanphilip 1278assessingstatewidehivpreexposureprophylaxisimplementationusinganallpayerclaimsdatabase AT chanphilip 1278assessingstatewidehivpreexposureprophylaxisimplementationusinganallpayerclaimsdatabase |